Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:
The method for the research-field-mapping can be reviewed here:
The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:
The present analysis is based on the following seed articles:
| AU | PY | TI | JI |
|---|---|---|---|
| SZPAKOWSKA M;DECKER AM;MEYR… | 2021 | THE NATURAL ANALGESIC CONOLIDINE TARGETS THE NEWLY IDENTIFIED OPIOID SCAVENGER ACKR3/CXCR7 | SIGNAL TRANSDUCT. TARGET. T… |
| GOLEBSKI K;LAYHADI JA;SAHIN… | 2021 | INDUCTION OF IL-10-PRODUCING TYPE 2 INNATE LYMPHOID CELLS BY ALLERGEN IMMUNOTHERAPY IS ASSOCIATED… | IMMUNITY |
| MEYRATH M;SZPAKOWSKA M;ZEIN… | 2020 | THE ATYPICAL CHEMOKINE RECEPTOR ACKR3/CXCR7 IS A BROAD-SPECTRUM SCAVENGER FOR OPIOID PEPTIDES | NAT. COMMUN. |
| KURNIAWAN H;FRANCHINA DG;GU… | 2020 | GLUTATHIONE RESTRICTS SERINE METABOLISM TO PRESERVE REGULATORY T CELL FUNCTION | CELL METAB. |
| MARTENS EC;NEUMANN M;DESAI MS | 2018 | INTERACTIONS OF COMMENSAL AND PATHOGENIC MICROORGANISMS WITH THE INTESTINAL MUCOSAL BARRIER | NAT. REV. MICROBIOL. |
Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.
Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_lih_dii.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.
Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA, Blei et al., 2003) is an example of topic model and is used to classify text in a document to a particular topic.
LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.
LDAvis is a web-based interactive visualisation of topics estimated using LDA (Sievert & Shirley, 2014). It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.
The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.
The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.
The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.
Note: This analysis refers the co-citation analysis,
where the cited references and not the original publications are the
unit of analysis. See tab Technical descriptionfor
additional explanations
In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.
| name | dgr_int | dgr |
|---|---|---|
| Knowledge Base 1: KB 1: unlabeled (n = 2515, density =2.12) | ||
| MARTENS E.C. CHIANG H.C. GORDON J.I. MUCOSAL GLYCAN FORAGING ENHANCES FITNESS AND TRANSMISSION OF A SACCHAROLYTIC HUMAN GUT BACTERIAL SYMBIONT (2008) | 2362 | 2561 |
| KOROPATKIN N.M. CAMERON E.A. MARTENS E.C. HOW GLYCAN METABOLISM SHAPES THE HUMAN GUT MICROBIOTA (2012) | 2306 | 2537 |
| EL KAOUTARI A. ARMOUGOM F. GORDON J.I. RAOULT D. HENRISSAT B. THE ABUNDANCE AND VARIETY OF CARBOHYDRATE-ACTIVE ENZYMES IN THE HUMAN GUT MICROBIOTA … | 1816 | 1916 |
| JOHANSSON M.E. PHILLIPSON M. PETERSSON J. VELCICH A. HOLM L. HANSSON G.C. THE INNER OF THE TWO MUC2 MUCIN-DEPENDENT MUCUS LAYERS IN COLON IS DEVOID… | 1351 | 1423 |
| SONNENBURG E.D. SMITS S.A. TIKHONOV M. HIGGINBOTTOM S.K. WINGREEN N.S. SONNENBURG J.L. DIET-INDUCED EXTINCTIONS IN THE GUT MICROBIOTA COMPOUND OVER… | 1254 | 1310 |
| TAILFORD L.E. CROST E.H. KAVANAUGH D. JUGE N. MUCIN GLYCAN FORAGING IN THE HUMAN GUT MICROBIOME (2015) | 1201 | 1273 |
| FURUSAWA Y. OBATA Y. FUKUDA S. ENDO T.A. NAKATO G. TAKAHASHI D. COMMENSAL MICROBE-DERIVED BUTYRATE INDUCES THE DIFFERENTIATION OF COLONIC REGULATOR… | 1053 | 1692 |
| ROUND J.L. MAZMANIAN S.K. INDUCIBLE FOXP3+ REGULATORY T-CELL DEVELOPMENT BY A COMMENSAL BACTERIUM OF THE INTESTINAL MICROBIOTA (2010) | 1046 | 1368 |
| KOROPATKIN N.M. MARTENS E.C. GORDON J.I. SMITH T.J. STARCH CATABOLISM BY A PROMINENT HUMAN GUT SYMBIONT IS DIRECTED BY THE RECOGNITION OF AMYLOSE H… | 1020 | 1044 |
| FURUSAWA Y. OBATA Y. FUKUDA S. ENDO T.A. NAKATO G. TAKAHASHI D. NAKANISHI Y. KATO T. COMMENSAL MICROBE-DERIVED BUTYRATE INDUCES THE DIFFERENTIATION… | 1006 | 1093 |
| Knowledge Base 2: KB 2: unlabeled (n = 1515, density =5.23) | ||
| MACIVER N.J. MICHALEK R.D. RATHMELL J.C. METABOLIC REGULATION OF T LYMPHOCYTES (2013) | 2627 | 2844 |
| MICHALEK R.D. GERRIETS V.A. JACOBS S.R. MACINTYRE A.N. MACIVER N.J. MASON E.F. SULLIVAN S.A. RATHMELL J.C. CUTTING EDGE: DISTINCT GLYCOLYTIC AND LI… | 2223 | 2499 |
| ZENG H. YANG K. CLOER C. NEALE G. VOGEL P. CHI H. MTORC1 COUPLES IMMUNE SIGNALS AND METABOLIC PROGRAMMING TO ESTABLISH T(REG) | 2144 | 3046 |
| PEARCE E.L. POFFENBERGER M.C. CHANG C.H. JONES R.G. FUELING IMMUNITY: INSIGHTS INTO METABOLISM AND LYMPHOCYTE FUNCTION (2013) | 1651 | 1904 |
| SHI L.Z. WANG R. HUANG G. VOGEL P. NEALE G. GREEN D.R. CHI H. HIF1ALPHA-DEPENDENT GLYCOLYTIC PATHWAY ORCHESTRATES A METABOLIC CHECKPOINT FOR THE DI… | 1605 | 1774 |
| SINCLAIR L.V. ROLF J. EMSLIE E. SHI Y.B. TAYLOR P.M. CANTRELL D.A. CONTROL OF AMINO-ACID TRANSPORT BY ANTIGEN RECEPTORS COORDINATES THE METABOLIC R… | 1556 | 1754 |
| SHI L.Z. WANG R. HUANG G. VOGEL P. NEALE G. GREEN D.R. HIF1ALPHA-DEPENDENT GLYCOLYTIC PATHWAY ORCHESTRATES A METABOLIC CHECKPOINT FOR THE DIFFERENT… | 1547 | 2001 |
| PENG M. YIN N. CHHANGAWALA S. XU K. LESLIE C.S. LI M.O. AEROBIC GLYCOLYSIS PROMOTES T HELPER 1 CELL DIFFERENTIATION THROUGH AN EPIGENETIC MECHANISM… | 1501 | 1650 |
| MICHALEK R.D. GERRIETS V.A. JACOBS S.R. MACINTYRE A.N. MACIVER N.J. MASON E.F. CUTTING EDGE: DISTINCT GLYCOLYTIC AND LIPID OXIDATIVE METABOLIC PROG… | 1441 | 1753 |
| BUCK M.D. O’SULLIVAN D. PEARCE E.L. T CELL METABOLISM DRIVES IMMUNITY (2015) | 1397 | 1538 |
| Knowledge Base 3: KB 3: unlabeled (n = 1400, density =4.88) | ||
| HORI S. NOMURA T. SAKAGUCHI S. CONTROL OF REGULATORY T CELL DEVELOPMENT BY THE TRANSCRIPTION FACTOR FOXP3 (2003) | 6308 | 7084 |
| FONTENOT J.D. GAVIN M.A. RUDENSKY A.Y. FOXP3 PROGRAMS THE DEVELOPMENT AND FUNCTION OF CD4+CD25+ REGULATORY T CELLS (2003) | 5095 | 5664 |
| ZHENG Y. JOSEFOWICZ S. CHAUDHRY A. PENG X.P. FORBUSH K. RUDENSKY A.Y. ROLE OF CONSERVED NON-CODING DNA ELEMENTS IN THE FOXP3 GENE IN REGULATORY T-C… | 1994 | 2336 |
| SAKAGUCHI S. SAKAGUCHI N. ASANO M. ITOH M. TODA M. IMMUNOLOGIC SELF-TOLERANCE MAINTAINED BY ACTIVATED T CELLS EXPRESSING IL-2 RECEPTOR ALPHA-CHAINS… | 1742 | 2055 |
| JOSEFOWICZ S.Z. LU L.F. RUDENSKY A.Y. REGULATORY T CELLS: MECHANISMS OF DIFFERENTIATION AND FUNCTION (2012) | 1694 | 2050 |
| KHATTRI R. COX T. YASAYKO S.A. RAMSDELL F. AN ESSENTIAL ROLE FOR SCURFIN IN CD4+CD25+ T REGULATORY CELLS (2003) | 1576 | 1655 |
| SAKAGUCHI S. YAMAGUCHI T. NOMURA T. ONO M. REGULATORY T CELLS AND IMMUNE TOLERANCE (2008) | 1407 | 1575 |
| LI X. LIANG Y. LEBLANC M. BENNER C. ZHENG Y. FUNCTION OF A FOXP3 CIS-ELEMENT IN PROTECTING REGULATORY T CELL IDENTITY (2014) | 1192 | 1329 |
| LEVINE A.G. ARVEY A. JIN W. RUDENSKY A.Y. CONTINUOUS REQUIREMENT FOR THE TCR IN REGULATORY T CELL FUNCTION (2014) | 957 | 1059 |
| FENG Y. ARVEY A. CHINEN T. VAN DER VEEKEN J. GASTEIGER G. RUDENSKY A.Y. CONTROL OF THE INHERITANCE OF REGULATORY T CELL IDENTITY BY A CIS ELEMENT I… | 949 | 1088 |
| Knowledge Base 4: KB 4: unlabeled (n = 1279, density =5.5) | ||
| LOCASALE J.W. SERINE GLYCINE AND ONE-CARBON UNITS: CANCER METABOLISM IN FULL CIRCLE (2013) | 2513 | 2619 |
| DUCKER G.S. RABINOWITZ J.D. ONE-CARBON METABOLISM IN HEALTH AND DISEASE (2017) | 1728 | 1793 |
| POSSEMATO R. MARKS K.M. SHAUL Y.D. PACOLD M.E. KIM D. BIRSOY K. SETHUMADHAVAN S. JHA A.K. FUNCTIONAL GENOMICS REVEAL THAT THE SERINE SYNTHESIS PATH… | 1661 | 1718 |
| LOCASALE J.W. GRASSIAN A.R. MELMAN T. LYSSIOTIS C.A. MATTAINI K.R. BASS A.J. HEFFRON G. SHARFI H. PHOSPHOGLYCERATE DEHYDROGENASE DIVERTS GLYCOLYTIC… | 1653 | 1721 |
| FAN J. YE J. KAMPHORST J.J. SHLOMI T. THOMPSON C.B. RABINOWITZ J.D. QUANTITATIVE FLUX ANALYSIS REVEALS FOLATE-DEPENDENT NADPH PRODUCTION (2014) | 1503 | 1568 |
| TIBBETTS A.S. APPLING D.R. COMPARTMENTALIZATION OF MAMMALIAN FOLATE-MEDIATED ONE-CARBON METABOLISM (2010) | 1502 | 1525 |
| MADDOCKS O.D. BERKERS C.R. MASON S.M. ZHENG L. BLYTH K. GOTTLIEB E. VOUSDEN K.H. SERINE STARVATION INDUCES STRESS AND P53-DEPENDENT METABOLIC REMOD… | 1336 | 1370 |
| LABUSCHAGNE C.F. VAN DEN BROEK N.J. MACKAY G.M. VOUSDEN K.H. MADDOCKS O.D. SERINE BUT NOT GLYCINE SUPPORTS ONE-CARBON METABOLISM AND PROLIFERATION … | 1257 | 1278 |
| VANDER HEIDEN M.G. CANTLEY L.C. THOMPSON C.B. UNDERSTANDING THE WARBURG EFFECT: THE METABOLIC REQUIREMENTS OF CELL PROLIFERATION (2009) | 1235 | 2524 |
| YANG M. VOUSDEN K.H. SERINE AND ONE-CARBON METABOLISM IN CANCER (2016) | 1233 | 1298 |
| Knowledge Base 5: KB 5: unlabeled (n = 1238, density =5.87) | ||
| COX L. NELSON H. LOCKEY R. CALABRIA C. CHACKO T. FINEGOLD I. ALLERGEN IMMUNOTHERAPY: A PRACTICE PARAMETER THIRD UPDATE (2011) | 1118 | 1124 |
| CANONICA G.W. COX L. PAWANKAR R. SUBLINGUAL IMMUNOTHERAPY: WORLD ALLERGY ORGANIZATION POSITION PAPER 2013 UPDATE (2014) | 999 | 999 |
| AKDIS M. AKDIS C.A. MECHANISMS OF ALLERGEN-SPECIFIC IMMUNOTHERAPY: MULTIPLE SUPPRESSOR FACTORS AT WORK IN IMMUNE TOLERANCE TO ALLERGENS (2014) | 945 | 986 |
| JUTEL M. JAEGER L. SUCK R. MEYER H. FIEBIG H. CROMWELL O. ALLERGEN-SPECIFIC IMMUNOTHERAPY WITH RECOMBINANT GRASS POLLEN ALLERGENS (2005) | 916 | 937 |
| DURHAM S.R. EMMINGER W. KAPP A. SQ-STANDARDIZED SUBLINGUAL GRASS IMMUNOTHERAPY: CONFIRMATION OF DISEASE MODIFICATION 2 YEARS AFTER 3 YEARS OF TREAT… | 913 | 913 |
| CANONICA G.W. COX L. PAWANKAR R. BAENA-CAGNANI C.E. BLAISS M. BONINI S. SUBLINGUAL IMMUNOTHERAPY: WORLD ALLERGY ORGANIZATION POSITION PAPER 2013 UP… | 906 | 906 |
| SHAMJI M.H. DURHAM S.R. MECHANISMS OF ALLERGEN IMMUNOTHERAPY FOR INHALED ALLERGENS AND PREDICTIVE BIOMARKERS (2017) | 853 | 880 |
| DURHAM S.R. EMMINGER W. KAPP A. DE MONCHY J.G. RAK S. SCADDING G.K. SQ-STANDARDIZED SUBLINGUAL GRASS IMMUNOTHERAPY: CONFIRMATION OF DISEASE MODIFIC… | 844 | 847 |
| DURHAM S.R. WALKER S.M. VARGA E.M. LONG-TERM CLINICAL EFFICACY OF GRASS-POLLEN IMMUNOTHERAPY (1999) | 840 | 843 |
| BLAISS M. MALONEY J. NOLTE H. GAWCHIK S. YAO R. SKONER D.P. EFFICACY AND SAFETY OF TIMOTHY GRASS ALLERGY IMMUNOTHERAPY TABLETS IN NORTH AMERICAN CH… | 830 | 830 |
| Knowledge Base 6: KB 6: unlabeled (n = 1137, density =7.84) | ||
| GASTEIGER G. FAN X. DIKIY S. LEE S.Y. RUDENSKY A.Y. TISSUE RESIDENCY OF INNATE LYMPHOID CELLS IN LYMPHOID AND NONLYMPHOID ORGANS (2015) | 2297 | 2310 |
| BARTEMES K.R. KEPHART G.M. FOX S.J. KITA H. ENHANCED INNATE TYPE 2 IMMUNE RESPONSE IN PERIPHERAL BLOOD FROM PATIENTS WITH ASTHMA (2014) | 1535 | 1535 |
| SILVER J.S. KEARLEY J. COPENHAVER A.M. SANDEN C. MORI M. YU L. INFLAMMATORY TRIGGERS ASSOCIATED WITH EXACERBATIONS OF COPD ORCHESTRATE PLASTICITY O… | 1452 | 1461 |
| DOHERTY T.A. KHORRAM N. LUND S. MEHTA A.K. CROFT M. BROIDE D.H. LUNG TYPE 2 INNATE LYMPHOID CELLS EXPRESS CYSTEINYL LEUKOTRIENE RECEPTOR 1 WHICH RE… | 1210 | 1210 |
| CONSTANTINIDES M.G. MCDONALD B.D. VERHOEF P.A. BENDELAC A. A COMMITTED PRECURSOR TO INNATE LYMPHOID CELLS (2014) | 1206 | 1210 |
| ARTIS D. SPITS H. THE BIOLOGY OF INNATE LYMPHOID CELLS (2015) | 1189 | 1265 |
| LAO-ARAYA M. STEVELING E. SCADDING G.W. DURHAM S.R. SHAMJI M.H. SEASONAL INCREASES IN PERIPHERAL INNATE LYMPHOID TYPE 2 CELLS ARE INHIBITED BY SUBC… | 1118 | 1606 |
| VIVIER E. ARTIS D. COLONNA M. DIEFENBACH A. DI SANTO J.P. EBERL G. INNATE LYMPHOID CELLS: 10 YEARS ON (2018) | 1079 | 1079 |
| OHNE Y. SILVER J.S. THOMPSON-SNIPES L. COLLET M.A. BLANCK J.P. CANTAREL B.L. IL-1 IS A CRITICAL REGULATOR OF GROUP 2 INNATE LYMPHOID CELL FUNCTION … | 918 | 918 |
| VON MOLTKE J. JI M. LIANG H.E. LOCKSLEY R.M. TUFT-CELL-DERIVED IL-25 REGULATES AN INTESTINAL ILC2-EPITHELIAL RESPONSE CIRCUIT (2016) | 911 | 1254 |
| Knowledge Base 7: KB 7: unlabeled (n = 1055, density =4.15) | ||
| LEVOYE A. BALABANIAN K. BALEUX F. BACHELERIE F. LAGANE B. CXCR7 HETERODIMERIZES WITH CXCR4 AND REGULATES CXCL12-MEDIATED G PROTEIN SIGNALING (2009) | 2270 | 2283 |
| LUKER K.E. STEELE J.M. MIHALKO L.A. RAY P. LUKER G.D. CONSTITUTIVE AND CHEMOKINE-DEPENDENT INTERNALIZATION AND RECYCLING OF CXCR7 IN BREAST CANCER … | 900 | 903 |
| ZLOTNIK A. YOSHIE O. THE CHEMOKINE SUPERFAMILY REVISITED (2012) | 815 | 821 |
| BURNS J.M. SUMMERS B.C. WANG Y. MELIKIAN A. BERAHOVICH R. MIAO Z. A NOVEL CHEMOKINE RECEPTOR FOR SDF-1 AND I-TAC INVOLVED IN CELL SURVIVAL CELL ADH… | 799 | 802 |
| DISSOCIATION OF CXCR4 ACTIVATION FROM BINDING AND INHIBITION OF HIV-1 (1997) | 754 | 760 |
| GRIFFITH J.W. SOKOL C.L. LUSTER A.D. CHEMOKINES AND CHEMOKINE RECEPTORS: POSITIONING CELLS FOR HOST DEFENSE AND IMMUNITY (2014) | 644 | 651 |
| KALATSKAYA I. BERCHICHE Y.A. GRAVEL S. LIMBERG B.J. ROSENBAUM J.S. HEVEKER N. AMD3100 IS A CXCR7 LIGAND WITH ALLOSTERIC AGONIST PROPERTIES (2009) | 644 | 644 |
| GRAHAM G.J. LOCATI M. MANTOVANI A. ROT A. THELEN M. THE BIOCHEMISTRY AND BIOLOGY OF THE ATYPICAL CHEMOKINE RECEPTORS (2012) | 519 | 519 |
| ZLOTNIK A. YOSHIE O. CHEMOKINES: A NEW CLASSIFICATION SYSTEM AND THEIR ROLE IN IMMUNITY (2000) | 497 | 497 |
| NAUMANN U. CAMERONI E. PRUENSTER M. MAHABALESHWAR H. RAZ E. ZERWES H.G. ROT A. THELEN M. CXCR7 FUNCTIONS AS A SCAVENGER FOR CXCL12 AND CXCL11 (2010) | 475 | 475 |
| Knowledge Base 8: KB 8: unlabeled (n = 713, density =8.23) | ||
| FURUSAWA Y. COMMENSAL MICROBE-DERIVED BUTYRATE INDUCES THE DIFFERENTIATION OF COLONIC REGULATORY T CELLS (2013) | 1485 | 1761 |
| SMITH P.M. THE MICROBIAL METABOLITES SHORT-CHAIN FATTY ACIDS REGULATE COLONIC TREG CELL HOMEOSTASIS (2013) | 1095 | 1276 |
| IVANOV I.I. INDUCTION OF INTESTINAL TH17 CELLS BY SEGMENTED FILAMENTOUS BACTERIA (2009) | 989 | 1111 |
| DAVID L.A. DIET RAPIDLY AND REPRODUCIBLY ALTERS THE HUMAN GUT MICROBIOME (2014) | 813 | 942 |
| ATARASHI K. TREG INDUCTION BY A RATIONALLY SELECTED MIXTURE OF CLOSTRIDIA STRAINS FROM THE HUMAN MICROBIOTA (2013) | 765 | 918 |
| ARPAIA N. METABOLITES PRODUCED BY COMMENSAL BACTERIA PROMOTE PERIPHERAL REGULATORY T-CELL GENERATION (2013) | 703 | 886 |
| ATARASHI K. INDUCTION OF COLONIC REGULATORY T CELLS BY INDIGENOUS CLOSTRIDIUM SPECIES (2011) | 670 | 770 |
| NG K.M. MICROBIOTA-LIBERATED HOST SUGARS FACILITATE POST-ANTIBIOTIC EXPANSION OF ENTERIC PATHOGENS (2013) | 640 | 747 |
| STRUCTURE FUNCTION AND DIVERSITY OF THE HEALTHY HUMAN MICROBIOME (2012) | 631 | 1512 |
| BUFFIE C.G. PRECISION MICROBIOME RECONSTITUTION RESTORES BILE ACID MEDIATED RESISTANCE TO CLOSTRIDIUM DIFFICILE (2015) | 574 | 611 |
| Knowledge Base 9: KB 9: unlabeled (n = 654, density =5.73) | ||
| AL-HASANI R. BRUCHAS M.R. MOLECULAR MECHANISMS OF OPIOID RECEPTOR-DEPENDENT SIGNALING AND BEHAVIOR (2011) | 409 | 409 |
| BOHN L.M. GAINETDINOV R.R. LIN F.T. LEFKOWITZ R.J. CARON M.G. MU-OPIOID RECEPTOR DESENSITIZATION BY BETA-ARRESTIN-2 DETERMINES MORPHINE TOLERANCE B… | 373 | 373 |
| BOHN L.M. LEFKOWITZ R.J. GAINETDINOV R.R. PEPPEL K. CARON M.G. LIN F.T. ENHANCED MORPHINE ANALGESIA IN MICE LACKING BETA-ARRESTIN 2 (1999) | 358 | 358 |
| GUREVICH E.V. GUREVICH V.V. ARRESTINS ARE UBIQUITOUS REGULATORS OF CELLULAR SIGNALING PATHWAYS (2006) | 324 | 324 |
| PETERSON Y.K. LUTTRELL L.M. THE DIVERSE ROLES OF ARRESTIN SCAFFOLDS IN G PROTEIN-COUPLED RECEPTOR SIGNALING (2017) | 310 | 310 |
| CARPENTER B. NEHMÉ R. WARNE T. LESLIE A.G. TATE C.G. STRUCTURE OF THE ADENOSINE A(2A) | 302 | 302 |
| SCHMID C.L. KENNEDY N.M. ROSS N.C. LOVELL K.M. YUE Z. MORGENWECK J. CAMERON M.D. BOHN L.M. BIAS FACTOR AND THERAPEUTIC WINDOW CORRELATE TO PREDICT … | 295 | 295 |
| SONG X. COFFA S. FU H. GUREVICH V.V. HOW DOES ARRESTIN ASSEMBLE MAPKS INTO A SIGNALING COMPLEX? (2009) | 292 | 292 |
| INDRISCHEK H. PROHASKA S.J. GUREVICH V.V. GUREVICH E.V. STADLER P.F. UNCOVERING MISSING PIECES: DUPLICATION AND DELETION HISTORY OF ARRESTINS IN DE… | 285 | 285 |
| GUREVICH V.V. GUREVICH E.V. THE MOLECULAR ACROBATICS OF ARRESTIN ACTIVATION (2004) | 280 | 280 |
In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).
\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]
The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.
This is arguably the more interesting part. Here, we identify the
literature’s current knowledge frontier by carrying out a bibliographic
coupling analysis of the publications in our corpus. This measure uses
bibliographical information of publications to establish a similarity
relationship between them. Again, method details to be found in the tab
Technical description. As you will see, we identify the
main research area, but also a set of adjacent research areas with some
theoretical/methodological/application overlap.
To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.
| label | AU | PY | TI | dgr_int | TC | TC_year |
|---|---|---|---|---|---|---|
| Research Area 1: RA 1: unlabeled (n = 1077, density =0.15) | ||||||
| RA 1: unlabeled | KOH A;DE VADDER F;KOVA… | 2016 | FROM DIETARY FIBER TO HOST PHYSIOLOGY: SHORT-CHAIN FATTY ACIDS AS KEY BACTERIAL METABOLITES | 3.34 | 2285 | 380.83 |
| RA 1: unlabeled | THURSBY E;JUGE N | 2017 | INTRODUCTION TO THE HUMAN GUT MICROBIOTA | 5.11 | 995 | 199.00 |
| RA 1: unlabeled | SONNENBURG JL;BÄCKHED F | 2016 | DIET-MICROBIOTA INTERACTIONS AS MODERATORS OF HUMAN METABOLISM | 4.15 | 1067 | 177.83 |
| RA 1: unlabeled | DESAI MS;SEEKATZ AM;KO… | 2016 | A DIETARY FIBER-DEPRIVED GUT MICROBIOTA DEGRADES THE COLONIC MUCUS BARRIER AND ENHANCES PATHOGEN SUSCEPTIBILITY | 4.10 | 1077 | 179.50 |
| RA 1: unlabeled | ROOKS MG;GARRETT WS | 2016 | GUT MICROBIOTA, METABOLITES AND HOST IMMUNITY | 2.85 | 1323 | 220.50 |
| RA 1: unlabeled | LEVY M;KOLODZIEJCZYK A… | 2017 | DYSBIOSIS AND THE IMMUNE SYSTEM | 4.50 | 622 | 124.40 |
| RA 1: unlabeled | MAKKI K;DEEHAN EC;WALT… | 2018 | THE IMPACT OF DIETARY FIBER ON GUT MICROBIOTA IN HOST HEALTH AND DISEASE | 3.25 | 804 | 201.00 |
| RA 1: unlabeled | THAISS CA;ZMORA N;LEVY… | 2016 | THE MICROBIOME AND INNATE IMMUNITY | 2.37 | 927 | 154.50 |
| RA 1: unlabeled | BELKAID Y;HARRISON OJ | 2017 | HOMEOSTATIC IMMUNITY AND THE MICROBIOTA | 4.36 | 495 | 99.00 |
| RA 1: unlabeled | BAÜMLER AJ;SPERANDIO V | 2016 | INTERACTIONS BETWEEN THE MICROBIOTA AND PATHOGENIC BACTERIA IN THE GUT | 3.07 | 595 | 99.17 |
| Research Area 2: RA 2: unlabeled (n = 580, density =0.33) | ||||||
| RA 2: unlabeled | O’NEILL LAJ;KISHTON RJ… | 2016 | A GUIDE TO IMMUNOMETABOLISM FOR IMMUNOLOGISTS | 2.40 | 1262 | 210.33 |
| RA 2: unlabeled | BUCK MD;SOWELL RT;KAEC… | 2017 | METABOLIC INSTRUCTION OF IMMUNITY | 3.57 | 549 | 109.80 |
| RA 2: unlabeled | SUKUMAR M;LIU J;MEHTA … | 2016 | MITOCHONDRIAL MEMBRANE POTENTIAL IDENTIFIES CELLS WITH ENHANCED STEMNESS FOR CELLULAR THERAPY | 6.69 | 201 | 33.50 |
| RA 2: unlabeled | KISHTON RJ;SUKUMAR M;R… | 2017 | METABOLIC REGULATION OF T CELL LONGEVITY AND FUNCTION IN TUMOR IMMUNOTHERAPY | 5.28 | 199 | 39.80 |
| RA 2: unlabeled | JOHNSON MO;WOLF MM;MAD… | 2018 | DISTINCT REGULATION OF TH17 AND TH1 CELL DIFFERENTIATION BY GLUTAMINASE-DEPENDENT METABOLISM | 3.86 | 243 | 60.75 |
| RA 2: unlabeled | LOFTUS RM;FINLAY DK | 2016 | IMMUNOMETABOLISM: CELLULAR METABOLISM TURNS IMMUNE REGULATOR | 3.23 | 238 | 39.67 |
| RA 2: unlabeled | ALMEIDA L;LOCHNER M;BE… | 2016 | METABOLIC PATHWAYS IN T CELL ACTIVATION AND LINEAGE DIFFERENTIATION | 2.98 | 217 | 36.17 |
| RA 2: unlabeled | NEWTON R;PRIYADHARSHIN… | 2016 | IMMUNOMETABOLISM OF REGULATORY T CELLS | 3.24 | 196 | 32.67 |
| RA 2: unlabeled | MENK AV;SCHARPING NE;M… | 2018 | EARLY TCR SIGNALING INDUCES RAPID AEROBIC GLYCOLYSIS ENABLING DISTINCT ACUTE T CELL EFFECTOR FUNCTIONS | 3.54 | 178 | 44.50 |
| RA 2: unlabeled | GERRIETS VA;KISHTON RJ… | 2016 | FOXP3 AND TOLL-LIKE RECEPTOR SIGNALING BALANCE T REG CELL ANABOLIC METABOLISM FOR SUPPRESSION | 2.28 | 276 | 46.00 |
| Research Area 3: RA 3: unlabeled (n = 462, density =0.81) | ||||||
| RA 3: unlabeled | CHINEN T;KANNAN AK;LEV… | 2016 | AN ESSENTIAL ROLE FOR THE IL-2 RECEPTOR IN T REG CELL FUNCTION | 7.08 | 393 | 65.50 |
| RA 3: unlabeled | KAMADA T;TOGASHI Y;TAY… | 2019 | PD-1+ REGULATORY T CELLS AMPLIFIED BY PD-1 BLOCKADE PROMOTE HYPERPROGRESSION OF CANCER | 6.44 | 361 | 120.33 |
| RA 3: unlabeled | TOGASHI Y;SHITARA K;NI… | 2019 | REGULATORY T CELLS IN CANCER IMMUNOSUPPRESSION — IMPLICATIONS FOR ANTICANCER THERAPY | 4.81 | 440 | 146.67 |
| RA 3: unlabeled | DOMINGUEZ-VILLAR M;HAF… | 2018 | REGULATORY T CELLS IN AUTOIMMUNE DISEASE | 7.24 | 282 | 70.50 |
| RA 3: unlabeled | MAJ T;WANG W;CRESPO J;… | 2017 | OXIDATIVE STRESS CONTROLS REGULATORY T CELL APOPTOSIS AND SUPPRESSOR ACTIVITY AND PD-L1-BLOCKADE RESISTANCE IN TUMOR | 5.27 | 341 | 68.20 |
| RA 3: unlabeled | LI MO;RUDENSKY AY | 2016 | T CELL RECEPTOR SIGNALLING IN THE CONTROL OF REGULATORY T CELL DIFFERENTIATION AND FUNCTION | 6.37 | 269 | 44.83 |
| RA 3: unlabeled | WING JB;TANAKA A;SAKAG… | 2019 | HUMAN FOXP3 + REGULATORY T CELL HETEROGENEITY AND FUNCTION IN AUTOIMMUNITY AND CANCER | 6.51 | 250 | 83.33 |
| RA 3: unlabeled | PLITAS G;RUDENSKY AY | 2016 | REGULATORY T CELLS: DIFFERENTIATION AND FUNCTION | 10.96 | 142 | 23.67 |
| RA 3: unlabeled | TAKEUCHI Y;NISHIKAWA H | 2016 | ROLES OF REGULATORY T CELLS IN CANCER IMMUNITY | 5.18 | 284 | 47.33 |
| RA 3: unlabeled | KITAGAWA Y;OHKURA N;KI… | 2017 | GUIDANCE OF REGULATORY T CELL DEVELOPMENT BY SATB1-DEPENDENT SUPER-ENHANCER ESTABLISHMENT | 7.20 | 184 | 36.80 |
| Research Area 4: RA 4: unlabeled (n = 462, density =0.45) | ||||||
| RA 4: unlabeled | PAVLOVA NN;THOMPSON CB | 2016 | THE EMERGING HALLMARKS OF CANCER METABOLISM | 3.16 | 2546 | 424.33 |
| RA 4: unlabeled | DUCKER GS;RABINOWITZ JD | 2017 | ONE-CARBON METABOLISM IN HEALTH AND DISEASE | 5.55 | 738 | 147.60 |
| RA 4: unlabeled | DE BERARDINIS RJ;CHAND… | 2016 | FUNDAMENTALS OF CANCER METABOLISM | 3.19 | 1281 | 213.50 |
| RA 4: unlabeled | VANDER HEIDEN MG;DEBER… | 2017 | UNDERSTANDING THE INTERSECTIONS BETWEEN METABOLISM AND CANCER BIOLOGY | 3.80 | 981 | 196.20 |
| RA 4: unlabeled | YANG M;VOUSDEN KH | 2016 | SERINE AND ONE-CARBON METABOLISM IN CANCER | 4.57 | 433 | 72.17 |
| RA 4: unlabeled | NEWMAN AC;MADDOCKS ODK | 2017 | ONE-CARBON METABOLISM IN CANCER | 9.27 | 189 | 37.80 |
| RA 4: unlabeled | LUENGO A;GUI DY;VANDER… | 2017 | TARGETING METABOLISM FOR CANCER THERAPY | 3.97 | 403 | 80.60 |
| RA 4: unlabeled | MATTAINI KR;SULLIVAN M… | 2016 | THE IMPORTANCE OF SERINE METABOLISM IN CANCER | 7.48 | 186 | 31.00 |
| RA 4: unlabeled | MA EH;BANTUG G;GRISS T… | 2017 | SERINE IS AN ESSENTIAL METABOLITE FOR EFFECTOR T CELL EXPANSION | 4.44 | 263 | 52.60 |
| RA 4: unlabeled | PACOLD ME;BRIMACOMBE K… | 2016 | A PHGDH INHIBITOR REVEALS COORDINATION OF SERINE SYNTHESIS AND ONE-CARBON UNIT FATE | 4.06 | 250 | 41.67 |
| Research Area 5: RA 5: unlabeled (n = 429, density =0.35) | ||||||
| RA 5: unlabeled | SHAMJI MH;DURHAM SR | 2017 | MECHANISMS OF ALLERGEN IMMUNOTHERAPY FOR INHALED ALLERGENS AND PREDICTIVE BIOMARKERS | 5.37 | 226 | 45.20 |
| RA 5: unlabeled | ROBERTS G;PFAAR O;AKDI… | 2018 | EAACI GUIDELINES ON ALLERGEN IMMUNOTHERAPY: ALLERGIC RHINOCONJUNCTIVITIS | 3.95 | 297 | 74.25 |
| RA 5: unlabeled | SHAMJI MH;KAPPEN JH;AK… | 2017 | BIOMARKERS FOR MONITORING CLINICAL EFFICACY OF ALLERGEN IMMUNOTHERAPY FOR ALLERGIC RHINOCONJUNCTIVITIS AND ALLERGIC ASTHMA… | 5.08 | 198 | 39.60 |
| RA 5: unlabeled | DEMOLY P;EMMINGER W;RE… | 2016 | EFFECTIVE TREATMENT OF HOUSE DUST MITE-INDUCED ALLERGIC RHINITIS WITH 2 DOSES OF THE SQ HDM SLIT-TABLET: RESULTS FROM A RA… | 3.82 | 146 | 24.33 |
| RA 5: unlabeled | DURHAM SR;PENAGOS M | 2016 | SUBLINGUAL OR SUBCUTANEOUS IMMUNOTHERAPY FOR ALLERGIC RHINITIS? | 5.32 | 100 | 16.67 |
| RA 5: unlabeled | VIRCHOW JC;BACKER V;KU… | 2016 | EFFICACY OF A HOUSE DUST MITE SUBLINGUAL ALLERGEN IMMUNOTHERAPY TABLET IN ADULTS WITH ALLERGIC ASTHMA: A RANDOMIZED CLINIC… | 1.46 | 257 | 42.83 |
| RA 5: unlabeled | SCADDING GW;CALDERON M… | 2017 | EFFECT OF 2 YEARS OF TREATMENT WITH SUBLINGUAL GRASS POLLEN IMMUNOTHERAPY ON NASAL RESPONSE TO ALLERGEN CHALLENGE AT 3 YEA… | 2.99 | 124 | 24.80 |
| RA 5: unlabeled | JUTEL M;AGACHE I;BONIN… | 2016 | INTERNATIONAL CONSENSUS ON ALLERGEN IMMUNOTHERAPY II: MECHANISMS, STANDARDIZATION, AND PHARMACOECONOMICS | 2.26 | 155 | 25.83 |
| RA 5: unlabeled | DHAMI S;NURMATOV U;ARA… | 2017 | ALLERGEN IMMUNOTHERAPY FOR ALLERGIC RHINOCONJUNCTIVITIS: A SYSTEMATIC REVIEW AND META-ANALYSIS | 1.89 | 167 | 33.40 |
| RA 5: unlabeled | NOLTE H;BERNSTEIN DI;N… | 2016 | EFFICACY OF HOUSE DUST MITE SUBLINGUAL IMMUNOTHERAPY TABLET IN NORTH AMERICAN ADOLESCENTS AND ADULTS IN A RANDOMIZED, PLAC… | 3.13 | 94 | 15.67 |
| Research Area 6: RA 6: unlabeled (n = 348, density =0.3) | ||||||
| RA 6: unlabeled | HUGHES CE;NIBBS RJB | 2018 | A GUIDE TO CHEMOKINES AND THEIR RECEPTORS | 1.61 | 345 | 86.25 |
| RA 6: unlabeled | JANSSENS R;STRUYF S;PR… | 2018 | THE UNIQUE STRUCTURAL AND FUNCTIONAL FEATURES OF CXCL12 | 2.98 | 129 | 32.25 |
| RA 6: unlabeled | POZZOBON T;GOLDONI G;V… | 2016 | CXCR4 SIGNALING IN HEALTH AND DISEASE | 3.04 | 124 | 20.67 |
| RA 6: unlabeled | BONECCHI R;GRAHAM GJ | 2016 | ATYPICAL CHEMOKINE RECEPTORS AND THEIR ROLES IN THE RESOLUTION OF THE INFLAMMATORY RESPONSE | 2.76 | 89 | 14.83 |
| RA 6: unlabeled | STONE MJ;HAYWARD JA;HU… | 2017 | MECHANISMS OF REGULATION OF THE CHEMOKINE-RECEPTOR NETWORK | 1.24 | 141 | 28.20 |
| RA 6: unlabeled | GIRBL T;LENN T;PEREZ L… | 2018 | DISTINCT COMPARTMENTALIZATION OF THE CHEMOKINES CXCL1 AND CXCL2 AND THE ATYPICAL RECEPTOR ACKR1 DETERMINE DISCRETE STAGES … | 1.20 | 127 | 31.75 |
| RA 6: unlabeled | MASSARA M;BONAVITA O;M… | 2016 | ATYPICAL CHEMOKINE RECEPTORS IN CANCER: FRIENDS OR FOES? | 2.51 | 54 | 9.00 |
| RA 6: unlabeled | HAO H;HU S;CHEN H;BU D… | 2017 | LOSS OF ENDOTHELIAL CXCR7 IMPAIRS VASCULAR HOMEOSTASIS AND CARDIAC REMODELING AFTER MYOCARDIAL INFARCTION: IMPLICATIONS FO… | 2.32 | 56 | 11.20 |
| RA 6: unlabeled | SZPAKOWSKA M;NEVINS AM… | 2018 | DIFFERENT CONTRIBUTIONS OF CHEMOKINE N-TERMINAL FEATURES ATTEST TO A DIFFERENT LIGAND BINDING MODE AND A BIAS TOWARDS ACTI… | 3.89 | 33 | 8.25 |
| RA 6: unlabeled | CHENG X;WANG H;ZHANG X… | 2017 | THE ROLE OF SDF-1/CXCR4/CXCR7 IN NEURONAL REGENERATION AFTER CEREBRAL ISCHEMIA | 2.03 | 62 | 12.40 |
| Research Area 7: RA 7: unlabeled (n = 311, density =0.42) | ||||||
| RA 7: unlabeled | VIVIER E;ARTIS D;COLON… | 2018 | INNATE LYMPHOID CELLS: 10 YEARS ON | 3.97 | 854 | 213.50 |
| RA 7: unlabeled | HABER AL;BITON M;ROGEL… | 2017 | A SINGLE-CELL SURVEY OF THE SMALL INTESTINAL EPITHELIUM | 0.93 | 632 | 126.40 |
| RA 7: unlabeled | COLONNA M | 2018 | INNATE LYMPHOID CELLS: DIVERSITY, PLASTICITY, AND UNIQUE FUNCTIONS IN IMMUNITY | 2.82 | 176 | 44.00 |
| RA 7: unlabeled | EBBO M;CRINIER A;VÉLY … | 2017 | INNATE LYMPHOID CELLS: MAJOR PLAYERS IN INFLAMMATORY DISEASES | 1.83 | 194 | 38.80 |
| RA 7: unlabeled | KABATA H;MORO K;KOYASU S | 2018 | THE GROUP 2 INNATE LYMPHOID CELL (ILC2) REGULATORY NETWORK AND ITS UNDERLYING MECHANISMS | 2.91 | 117 | 29.25 |
| RA 7: unlabeled | MORITA H;KUBO T;RÜCKER… | 2019 | INDUCTION OF HUMAN REGULATORY INNATE LYMPHOID CELLS FROM GROUP 2 INNATE LYMPHOID CELLS BY RETINOIC ACID | 3.69 | 86 | 28.67 |
| RA 7: unlabeled | BAL SM;GOLEBSKI K;SPITS H | 2020 | PLASTICITY OF INNATE LYMPHOID CELL SUBSETS | 2.62 | 111 | 55.50 |
| RA 7: unlabeled | PANDA SK;COLONNA M | 2019 | INNATE LYMPHOID CELLS IN MUCOSAL IMMUNITY | 3.01 | 94 | 31.33 |
| RA 7: unlabeled | CORTEZ VS;ULLAND TK;CE… | 2017 | SMAD4 IMPEDES THE CONVERSION OF NK CELLS INTO ILC1-LIKE CELLS BY CURTAILING NON-CANONICAL TGF-Β SIGNALING | 1.32 | 182 | 36.40 |
| RA 7: unlabeled | GURRAM RK;ZHU J | 2019 | ORCHESTRATION BETWEEN ILC2S AND TH2 CELLS IN SHAPING TYPE 2 IMMUNE RESPONSES | 3.53 | 66 | 22.00 |
| Research Area 8: RA 8: unlabeled (n = 236, density =0.27) | ||||||
| RA 8: unlabeled | WACKER D;STEVENS RC;RO… | 2017 | HOW LIGANDS ILLUMINATE GPCR MOLECULAR PHARMACOLOGY | 1.17 | 281 | 56.20 |
| RA 8: unlabeled | SMITH JS;LEFKOWITZ RJ;… | 2018 | BIASED SIGNALLING: FROM SIMPLE SWITCHES TO ALLOSTERIC MICROPROCESSORS | 0.71 | 327 | 81.75 |
| RA 8: unlabeled | WACKER D;WANG S;MCCORV… | 2017 | CRYSTAL STRUCTURE OF AN LSD-BOUND HUMAN SEROTONIN RECEPTOR | 1.13 | 202 | 40.40 |
| RA 8: unlabeled | INOUE A;RAIMONDI F;KAD… | 2019 | ILLUMINATING G-PROTEIN-COUPLING SELECTIVITY OF GPCRS | 1.10 | 171 | 57.00 |
| RA 8: unlabeled | GUREVICH VV;GUREVICH EV | 2019 | GPCR SIGNALING REGULATION: THE ROLE OF GRKS AND ARRESTINS | 1.02 | 182 | 60.67 |
| RA 8: unlabeled | KRISHNA KUMAR K;SHALEV… | 2019 | STRUCTURE OF A SIGNALING CANNABINOID RECEPTOR 1-G PROTEIN COMPLEX | 0.91 | 189 | 63.00 |
| RA 8: unlabeled | VALENTINO RJ;VOLKOW ND | 2018 | UNTANGLING THE COMPLEXITY OF OPIOID RECEPTOR FUNCTION | 1.15 | 115 | 28.75 |
| RA 8: unlabeled | CONIBEAR AE;KELLY E | 2019 | A BIASED VIEW OF Μ-OPIOID RECEPTORS? | 2.35 | 54 | 18.00 |
| RA 8: unlabeled | STAUS DP;HU H;ROBERTSO… | 2020 | STRUCTURE OF THE M2 MUSCARINIC RECEPTOR–Β-ARRESTIN COMPLEX IN A LIPID NANODISC | 1.03 | 121 | 60.50 |
| RA 8: unlabeled | KIM K;CHE T;PANOVA O;D… | 2020 | STRUCTURE OF A HALLUCINOGEN-ACTIVATED GQ-COUPLED 5-HT2A SEROTONIN RECEPTOR | 1.05 | 100 | 50.00 |
In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.
\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]
Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).
\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]
More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.
All results are preliminary so far…